Pharmaceutical Product Development

About: Pharmaceutical Product Development is a company organization based out in Wilmington, North Carolina, United States. It is known for research contribution in the topics: Immunotoxin & Fusion protein. The organization has 402 authors who have published 353 publications receiving 16396 citations.

A Bayesian sequential design with adaptive randomization for 2‐sided hypothesis test

Abstract: Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size.

Biomarkers in Clinical Trials for Rheumatoid Arthritis

Abstract: Rheumatoid arthritis is a complex systemic autoimmune disease that is characterized by chronic inflammatory polyarthritis, extra-articular features, and autoantibody formation. Although a targeted therapeutic approach using disease-modifying rheumatic drugs has markedly improved overall patient outcomes, there remain significant delays in accomplishing low disease activity in many patients. Reducing the numbers of patients needed for clinical trials is essential to the future of rheumatoid arthritis medical product development programs. Integration of biomarkers into clinical trials for rheumatoid arthritis may be helpful for early disease detection, patient stratification, and treatment response assessment. This goal has not yet been realized but can be achievable with good basic and applied research, systematic data collection, and data systems that can be used to integrate and share data. Herein, we explore what is currently known regarding biomarkers for rheumatoid arthritis and discuss issues to be addressed as biomarkers are sought for future development programs.

Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry.

Abstract: Objective: To implement a quality improvement based system to measure and improve data quality in an observational clinical registry to support a Learning Healthcare System. Data Source: ImproveCareNow Network registry, which as of September 2019 contained data from 314,250 visits of 43,305 pediatric Inflammatory Bowel Disease (IBD) patients at 109 participating care centers. Study Design: The impact of data quality improvement support to care centers was evaluated using statistical process control methodology. Data quality measures were defined, performance feedback of those measures using statistical process control charts was implemented, and reports that identified data items not following data quality checks were developed to enable centers to monitor and improve the quality of their data. Principal Findings: There was a pattern of improvement across measures of data quality. The proportion of visits with complete critical data increased from 72 percent to 82 percent. The percent of registered patients improved from 59 percent to 83 percent. Of three additional measures of data consistency and timeliness, one improved performance from 42 percent to 63 percent. Performance declined on one measure due to changes in network documentation practices and maturation. There was variation among care centers in data quality. Conclusions: A quality improvement based approach to data quality monitoring and improvement is feasible and effective.